Yu-Han Lyu

Papers

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About

Yu-Han Lyu’s research lies at the intersection of robotics, optimization, and probabilistic planning, with a focus on enabling resilient and efficient autonomous systems. Her major contributions include foundational work on the bench mover’s problem, where she derived analytical solutions for minimum-time trajectories under switching costs—a rare result that provides closed-form insights for robot motion planning. This work, cited 8 times, addresses a long-standing challenge in optimal control by simplifying complex differential equations into tractable trajectory classes. Lyu also pioneered the concept of k-survivability, a probabilistic metric for evaluating the resilience of multi-robot systems operating in stochastic threat environments. Her 2016 paper, cited 6 times, formalizes the trade-off between path diversity and survival probability, proving that maximizing k-survivability is NP-hard and offering algorithmic approaches for path selection. This work has practical implications for expendable robot swarms in hazardous settings, such as search-and-rescue or military reconnaissance. Lyu’s research is notable for bridging rigorous mathematical theory with real-world robotic constraints, making her a key voice in the growing field of risk-aware autonomous navigation.